相关论文: A Deep Learning Approach to Quasar Continuum Predi…

Current end-to-end machine reading and question answering (Q\&A) models are primarily based on recurrent neural networks (RNNs) with attention. Despite their success, these models are often slow for both training and inference due to the…

In wireless communication systems, the asynchronization of the oscillators in the transmitter and the receiver along with the Doppler shift due to relative movement may lead to the presence of carrier frequency offset (CFO) in the received…

We determine the 22$\mu$m luminosity evolution and luminosity function for quasars from a data set of over 20,000 objects obtained by combining flux-limited Sloan Digital Sky Survey optical and Wide field Infrared Survey Explorer…

As spectroscopic surveys continue to grow in size, the problem of classifying spectra targeted as quasars (QSOs) will need to move beyond its historical reliance on human experts. Instead, automatic classifiers will increasingly become the…

Quantum-inspired neural network is one of the interesting researches at the junction of the two fields of quantum computing and deep learning. Several models of quantum-inspired neurons with real parameters have been proposed, which are…

Quasars at the redshift frontier (z > 7.0) are fundamental probes of black hole (BH) growth and evolution but notoriously difficult to identify. At these redshifts, machine learning-based selection methods have proven to be efficient, but…

Quantum neural network (QNN) is one of the promising directions where the near-term noisy intermediate-scale quantum (NISQ) devices could find advantageous applications against classical resources. Recurrent neural networks are the most…

We design a convolutional neural network (CNN) incorporating channel attention and spatial attention mechanisms to predict atmospheric parameters of hot subdwarfs. The experimental dataset comprises spectra at nine distinct signal-to-noise…

We obtain a sample of 87 radio-loud QSOs in the redshift range 3.6<z<4.4 by cross-correlating sources in the FIRST radio survey S{1.4GHz} > 1 mJy with star-like objects having r <20.2 in SDSS Data Release 7. Of these 87 QSOs, 80 are…

Quantum machine learning, focusing on quantum neural networks (QNNs), remains a vastly uncharted field of study. Current QNN models primarily employ variational circuits on an ansatz or a quantum feature map, often requiring multiple…

The average flux decrement shortward the Ly$_{\alpha}$ emission, due to the well-known ``forest'' of absorptions, has been measured in the spectra of 8 quasars. Quasi-simultaneous optical and IUE observations of the two low redshift quasars…

Ultrafast ultrasound imaging remains an active area of interest in the ultrasound community due to its ultra-high frame rates. Recently, a wide variety of studies based on deep learning have sought to improve ultrafast ultrasound imaging.…

We match quasars discovered in a multi-color survey centered on the northern Hubble Deep Field (HDF) with radio sources from an ultra-deep radio survey. Although 3 out of 12 quasars are detected at a level below 0.2 mJy at 1.4 GHz, all of…

Strongly lensed quadruply imaged quasars (quads) are extraordinary objects. They are very rare in the sky -- only a few tens are known to date -- and yet they provide unique information about a wide range of topics, including the expansion…

We report the result of a faint quasar survey in a one square degree field. The aim is to test the Y-K/g-z and J-K/i-Y color selection criteria for quasars at faint magnitude, to obtain a complete sample of quasars based on deep optical and…

Quasar absorption line analysis is critical for studying gas and dust components and their physical and chemical properties as well as the evolution and formation of galaxies in the early universe. Ca II absorbers, which are one of the…

Quasar spectra carry the imprint of foreground intergalactic medium (IGM) through absorption features. In particular, absorption caused by neutral hydrogen gas, the ``Ly$\alpha$ forest,'' is a key spectroscopic tracer for cosmological…

We present a new Bayesian algorithm making use of Markov Chain Monte Carlo sampling that allows us to simultaneously estimate the unknown continuum level of each quasar in an ensemble of high-resolution spectra, as well as their common…

Deep learning (DL) has been shown to outperform traditional, human-defined summary statistics of the Ly{\alpha} forest in constraining key astrophysical and cosmological parameters owing to its ability to tap into the realm of non-Gaussian…

Upcoming widefield surveys, such as the Rubin Observatory's Legacy Survey of Space and Time (LSST), will monitor thousands of strongly lensed quasars over a 10 yr period. Many of these monitored quasars will undergo high-magnification…